Segmentation of Lung Tumors by Using SVM Classifier with Fuzzy Clustering Algorithm

Segmentation of Lung Tumors by Using SVM Classifier with Fuzzy Clustering Algorithm

Jalal deen K1 , Jayaprakasam K2

1Asst. Prof , Department of ECE, NPR College of Engg and Tech,Email : jalaldeenk@nprcolleges.org

2 Asst. Prof , Department of ECE, NPR College of Engg and Tech,Email :, jeya@nprcolleges.org

Abstract—     Tuberculosis is considered the main health threat in several parts of the world. This is the   primary infectious disease causing this disease. When untreated and undiagnosed, there is a high mortalityrate in patients.Thismethodincludes an automatic method to recognize tubers. This approach requires automated tuberculosis identification techniques to reduce problematic illnesses. Extraction of the lung region is first performed using the Graph Cut segmentation system. We develop a collection of properties including textures, shapes, etc. in this area of ​​the lung. You must use an SVM to identify X-rays as normal or abnormal. The systematic system proposed for analyzing TB segmentation provides better performance than the graph cut segmentation method.

Index Terms— ANN, Segmentation, fuzzy, graph cut, SVM.